code: def __init__(self, model_name="ResNet50", last_stride=1):
      super(ResNetEmbedding, self).__init__()
      assert model_name in [
          "ResNet50",
          "ResNet101",
      ], "Unsupported ReID arch: {}".format(model_name)
      self.base = eval(model_name)(last_conv_stride=last_stride)
      self.gap = nn.AdaptiveAvgPool2D(output_size=1)
      self.flatten = nn.Flatten(start_axis=1, stop_axis=-1)
      self.bn = nn.BatchNorm1D(self.in_planes, bias_attr=False)
  
file_path: PaddleDetection/ppdet/modeling/reid/resnet_embedding.py
imports: import os
  import paddle
  import paddle.nn.functional
  from paddle import nn
  from .resnet import ResNet50, ResNet101
  from ppdet.core.workspace import register
label_desc: Use image node_id 1 to create a new ResNetEmbedding object from inherited base classes: nn with example: obj = ResNetEmbedding(model_name, last_stride)